Top AI Jobs in Los Angeles, CA

Integrate and fine-tune existing AI models into product features, build evaluation frameworks and observability for production AI, collaborate with data science and engineering, and develop AI-powered application features using Python to improve user experience.

Build and operate an enterprise AI platform and integrations that connect LLMs to internal systems. Develop production AI applications, manage model/provider evaluations, ensure security/compliance for government environments, and deliver company-wide AI training and enablement.

Build and maintain AI platform infrastructure, connectors, API integrations, and custom AI-powered applications. Implement authentication, data pipelines, and tooling to embed LLM capabilities across teams. Contribute code, documentation, reviews, and enablement while ensuring security and compliance for government requirements.

Build and lead an enterprise AI platform: design infrastructure, integrations, and custom AI applications. Own provider/tool selection, deploy production model pipelines and connectors, ensure compliance with government security requirements, mentor engineers, and deliver company-wide AI enablement and training.

Develop and deploy machine learning systems for Mars missions, enhance atmospheric modeling, and integrate multi-modal data for autonomous science.

The role involves developing machine learning systems for Mars atmospheric modeling and multi-modal data fusion, contributing to autonomous science in space missions.

As an AI Engineer, you will build and scale AI business applications, focusing on generative AI. Responsibilities include rapid prototyping, applying software engineering best practices, and providing production support.

Design and implement AI capabilities, transition prototypes to production, build agent workflows, optimize data retrieval, and automate evaluation processes.

Lead design and delivery of production autonomous agents and agentic workflows: architect orchestration, integrate and optimize frontier LLMs, drive model fine-tuning and evaluation, mentor engineers, and translate business goals into safe, reliable, scalable AI-powered product experiences.

Lead GTM systems and applied AI for Revenue Operations: own non-Salesforce tech stack, drive GTM AI roadmap and COE, prototype and deploy AI workflows, govern data quality, optimize tooling, and manage a team of engineers and analysts.

Contractor will design, build, and deploy internal AI-enabled web applications and tools across frontend and backend stacks. Responsibilities include UI development, APIs, databases, LLM integrations, workflow automation, code review, security best practices, and collaborating with stakeholders to translate business needs into scalable, maintainable solutions.

Design, prototype, and deploy LLM-powered agents, RAG workflows, and automations that accelerate internal teams and customer-facing product features. Integrate AI systems with SaaS tools, build reusable components and evaluation frameworks, embed with business teams to deliver measurable outcomes, and establish standards for responsible AI, monitoring, and cost control across the company.

Build and operate Coinbase's LLM and agent platform: design the LLM gateway, agent runtime, knowledge bases, AI spend governance, observability/eval tooling, and ship production agents while partnering cross-functionally to ensure secure, cost-effective, and responsible generative AI at scale.

Design, build, and own production AI agents and automations for marketing. Integrate and instrument the marketing stack (Salesforce, HubSpot, Qualified, Clay, ZoomInfo, data warehouse), implement predictive scoring and personalization, monitor systems for reliability, and collaborate with marketing, RevOps, and sales to translate problems into deployable software.

The ERP AI Engineer - Manager at PwC leads teams in AI/ML engineering, manages client relationships, and designs AI solutions, all while mentoring team members and addressing complex business challenges.

Own enterprise AI strategy and launch the PureSpectrum AI Academy. Curate an approved AI tool stack, create function-level AI playbooks, manage an active AI project portfolio, partner with engineering to implement API-connected workflows, and drive measurable adoption, automation, efficiency, and ROI across functions while reporting program status to leadership.

Lead strategy and delivery of AI-powered, agentic product features for a SaaS insurance platform. Define roadmaps, KPIs, ROI, and success criteria; collaborate with engineering and data science to prototype, test, and launch; drive adoption, mentor junior PMs, and align cross-functional teams from discovery through GTM.

Build and operate Coinbase's LLM and agent platform: unified model gateway, AI Hub, secure microVM agent runtime, knowledge base integrations, AI FinOps, observability and evaluation tooling, and production-grade agent deployments with teams across the company.

The AI Automation Lead will architect and deliver multi-agent AI workflows, develop full-stack applications, and lead technical decisions across engineering teams.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

Design, build, deploy, and maintain scalable, resilient backend services for a Voice AI platform. Lead cross-cutting projects, make architectural decisions, integrate AI platforms, implement observability and evaluation frameworks, and mentor engineers.

Evaluate and validate AI Coach chat outputs for accuracy and risk, act as subject-matter expert in personal financial planning, identify enhancements, escalate issues to Ops/Product/Compliance, and contribute reusable solution libraries to improve member experience.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

Lead design and implementation of agentic AI workflows and integrations for Acquia DAM. Build, ship, and observe production AI features (auto-tagging, search, governance), set AI engineering standards, evaluate models and tooling, mentor engineers, and represent AI architecture to product and customers.

The AI Engineer Manager leads the Data and Analytics Engineering team in developing AI solutions, manages client accounts, analyzes data, and fosters team leadership and relationships with clients.